The objective of this proposal is to quantify the role of PSA screening in US prostate cancer incidence and mortality trends. Prostate cancer incidence and mortality in the US have been declining since the early 1990s. The role of PSA screening in the recent trends is a subject of intense debate. Information on the efficacy of PSA testing from controlled clinical trials is lacking, and researchers and the public are divided about how much information about the test can be gleaned from the observed trends. To address the need for a quantitative approach to linking population PSA testing and prostate cancer trends, the first specific aim of this proposal is to develop a computer microsimulation model to project the impact of PSA screening on US prostate cancer incidence and mortality. The model will first project population prostate cancer incidence and mortality in the absence of PSA screening. The model will then superimpose dissemination of PSA screening and the modeled population trends will be compared with those observed. Recognizing that a major driving force behind any population effect of screening is the speed with which screening is adopted in the population, the second specific aim is to model the dissemination of PSA screening in the US. We will use the SEER- Medicare data to estimate annual PSA screening rates for older men. For younger men, we will use data from a case-control study of prostate cancer incidence that interviewed participants about their PSA screening histories. The estimates of PSA dissemination will be used as inputs to the computer model. Early detection of prostate cancer is affected not only by the extent of screening but also by the ability of the test to identify latent cancers. This depends on the growth of PSA in prostate cancer cases which has been estimated in several studies. Since these studies yield somewhat inconsistent results, the third specific aim is to conduct a meta-analysis of the data available regarding PSA growth in prostate cancer cases. The results of the meta-analysis will be used to inform the microsimulation model about PSA growth in men with prostate cancer.